Automatic success tree-based reliability analysis for the consideration of transient and permanent faults

Success tree analysis is a well-known method to quantify the dependability features of many systems. This paper presents a system-level methodology to automatically generate a success tree from a given embedded system implementation and subsequently analyzes its reliability based on a state-of-the-art Monte Carlo simulation. This enables the efficient analysis of transient as well as permanent faults while considering methods such as task and resource redundancy to compensate these. As a case study, the proposed technique is compared with two analysis techniques, successfully applied at system level: (1) a BDD-based reliability analysis technique and (2) a SAT-assisted approach, both suffering from exponential complexity in either space or time. Experimental results performed on an extensive test suite show that: (a) Opposed to the Success Tree (ST) and SAT-assisted approaches, the BDD-based approach is highly vulnerable to exhaust available memory during its construction for moderate and large test cases. (b) The proposed ST technique is competitive to the SAT-assisted analysis in analysis speed and accuracy, while being the only technique that is suitable to also handle large and complex system implementations in which permanent and transient faults may occur concurrently.